Interrater agreement for sonographic stomach position classification in fetal diaphragmatic hernia across the North American Fetal Therapy Network
Bibliographic record
Abstract
Abstract Objective To evaluate inter‐rater agreement for sonographic classification of stomach position (as a surrogate for liver herniation) in fetal left congenital diaphragmatic hernia (LCDH) among: (i) fetal medicine specialists from the North American Fetal Therapy Network (NAFTNet) centers within and without the fetal endoscopic tracheal occlusion (FETO) consortium and in comparison to an expert external reviewer (ER1); and (iii) among two expert ERs (ER1 and ER2). Methods Forty‐eight physicians from 26 NAFTNet centers and 2 ERs were asked to assess 13 sonographic clips of isolated LCDH and classify stomach position as “intra‐abdominal,” “anterior left chest,” “mid to posterior left chest,” or “retro‐cardiac" based on the classification published by Basta et al. 8 Interrater agreement was assessed by determining proportion of stomach position ratings concordant amongst NAFTNet participants and ER1. Agreement for stomach position between ERs was calculated using kappa statistics. Results Agreement for stomach position was 69% (39%–85%; n = 19) and 54% (23%–92%; n = 29) among FETO and non‐FETO NAFTNet participants, respectively, when compared to ER1. Most disagreement in stomach position was related to a discrepancy of one position. ERs were in agreement for stomach position in 5 of 13 cases (38.5%) and inter‐rater agreement was highest for “anterior” stomach position. Conclusion Interrater agreement for stomach position assessment in CDH was poor across NAFTNet and indeed amongst expert reviewers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".